Description :

Type : Remote - 3 days in a month at (Noida/Bengaluru/Chennai/Hyderabad/Pune)

Experience : 6+ Years

Role Summary :

The Senior Data Analyst UHC Claims Platforms is a domain focused analytics role responsible for analyzing, validating, and interpreting healthcare claims data across United Healthcare claims platforms such as UNET, COSMOS, CSP, and Facets.

This role acts as a bridge between claims operations, analytics, and automation teams, ensuring that analytical outputs, dashboards, validation datasets, and AI models are grounded in real world claims processing logic and policy intent.

This role is critical in initiatives related to claims automation, first pass adjudication, rework reduction, quality improvement, and AI driven decisioning

Key Responsibilities :

Claims Domain Analytics :

- Perform deep dive analysis of medical and behavioral health claims data across UNET and COSMOS platforms.

- Understand and interpret end to end claims lifecycle, including intake, edits, pends, denials, adjustments, rework, and final adjudication.

- Analyze claim outcomes in relation to benefit configuration, policy rules, provider contracts, and member eligibility.

- Support analysis for first pass claims, auto adjudication, rework scenarios, and appeals.

Data Validation & SME Enablement :

- Validate datasets used for analytics, dashboards, and AI/ML model training against actual platform behavior.

- Identify gaps between policy intent and system execution by analyzing claim outcomes across platforms.

- Act as a claims SME for analytics, data science, and engineering teams, ensuring correct interpretation of UNET/COSMOS data elements.

- Support UAT and pilot evaluations for claims automation and AI initiatives by validating decision logic and outputs.

Analytics & Reporting :

- Build and maintain analytical datasets, metrics, and dashboards related to claims volume, quality, turnaround time, and auto adjudication performance.

- Analyze trends and patterns in claims data to identify leakage, quality issues, and automation opportunities.

- Support leadership reporting with accurate, explainable, and audit ready analytics derived from claims platforms.

Cross Functional Collaboration :

- Partner with Claims Operations, Product Owners, and Policy SMEs to translate operational processes into analytics requirements.

- Work closely with Data Engineers and ML Engineers to ensure claims data is correctly sourced, transformed, and interpreted.

- Participate in backlog refinement, requirements discussions, and solution reviews for claims automation programs.

Required Domain Experience :

- Strong hands on experience with UHC Claims platforms, specifically:

- UNET (claim processing, ARU/EAS logic, rework, adjustments)

- COSMOS (first pass claims, facility claims, claim edits)

- Solid understanding of : Claims edits, pends, denials, and rework flows

- Benefit application and policy logic

- Provider and member data relationships

- Experience working with claims related reference systems such as CSP, Facets, NDB, or CORE is highly desirable.

Technical & Analytical Skills :

- Strong SQL skills for querying large claims datasets.

- Experience working with enterprise data warehouses or analytics platforms.

- Ability to analyze complex datasets and translate findings into clear business insights.

- Working knowledge of Excel and BI tools for analysis and reporting.

- Familiarity with validation datasets used for AI/ML initiatives is a plus.

Qualifications :

- Bachelors degree or equivalent practical experience.

- 5+ years of experience in data analysis roles within healthcare or insurance domains.

- Demonstrated experience analyzing medical or behavioral health claims data within UHC env.

- Strong comm skills with the ability to explain complex claims logic to technical and non technical stakeholders.

Success Measures :

- Analytics and validation datasets accurately reflect real claims processing behavior.

- Claims automation and AI initiatives are supported by high quality, domain validated data.

- Reduction in defects caused by misinterpretation of claims data.

- Increased trust from claims operations & leadership in analytics outputs.